[unreadable] [unreadable] We propose to create an online computational tool called the Microbial Genome Informatics Platform (MGIP), which will analyze multi-locus sequence typing (MLST) and have comparative genomics functionality. MGIP will be able to categorize strains of Neisseria meningitidis using MLST and will facilitate epidemiological studies worldwide. MGIP will be able to compare all complete genomes of Neisseria meningitidis and N. gonorrhoeae, including four as-of-yet unpublished N. meningitidis [unreadable] strains that we are assembling. Therefore, it is imperative to develop computational support to match the load of incoming data. Bacterial meningitis has about a 10% fatality rate plus another 15% with long-term sequelae. In sub-Saharan Africa, there can be up to 400,000 reported cases per year. MGIP falls in line with the CDC's goals of "People Prepared for Emerging Health Threats" because it will facilitate worldwide epidemiological studies of meningococcus and accelerate crucial genetic studies of hypervirulent strains. [unreadable] [unreadable] [unreadable]